econdatar-package: Automation of Data Tasks to and from Codera Analytics'...

econdatar-packageR Documentation

Automation of Data Tasks to and from Codera Analytics' Econometric Data Services

Description

Automation of data tasks to and from <https://codera.co.za> econometric data services. Using this package users can download data from <https://www.econdata.co.za> directly into R (in tidy format) after signing up for a free account. <https://www.econdata.co.za> hosts a comprehensive database of South African macroeconomic data. For support and tutorials please see <https://econdata.co.za>.

Details

This package provides an interface to Codera Analytic's econometric data service (https://codera.co.za) and the EconData database (https://www.econdata.co.za) in particular.

EconData enables automation of analytical workflows that depend on public domain or third-party data. It is also a leading-edge forecast management system, enabling data and model automation and best practice data and model governance. EconData supports data-sharing across databases and within institutions, codifies modelling process flows and provides user-level access control. EconData makes it easy to securely manage and share model scenarios and forecast vintages.

The EconData Registry provides a central data glossary of data concepts and the information necessary to access and interpret data and associated metadata.

Codera also uses EconData to automate models, do research, and create value-added products such as interactive scenario dashboards. These dashboards and forecasts are made available to our clients.

Author(s)

Maintainer: Byron Botha <econdata@codera.co.za>

See Also

https://www.econdata.co.za https://econdata.co.za

Examples

## Not run: 
# library(econdatar)

# Return all data sets (useful for browsing available data)
CATALOGUE <- read_database(id = "all", tidy = TRUE)

# Mining production and sales
MINING <- read_dataset(id = "MINING", tidy = TRUE)

## End(Not run)

coderaanalytics/econdatar documentation built on Nov. 1, 2024, 5:41 a.m.